## ----setup, echo=FALSE, results='hide'----------------------------------- library("knitr") #opts_chunk$set(fig.align="center", fig.width=7, fig.height=7) #options(width=90) ## ----lib, message=FALSE, results='hide', warning=FALSE------------------- library(flowVS) #load library ## ----HD, echo=TRUE, warning=FALSE, fig.keep='high', fig.show='hold', out.width='.49\\linewidth', fig.cap='Transforming two fluorescence channels in the HD data. Bartlett\'s statistics (Y-axis) is computed from density peaks after data is transformed by different cofactors (X-axis). An optimum cofactor is obtained where Bartlett\'s statistics is minimum (indicated by red circles).'---- ## Example 1: Healthy data from flowVS package data(HD) ## identify optimum cofactor for CD3 and CD4 channels cofactors = estParamFlowVS(HD[1:5],channels=c('CD3', 'CD4')) ## ----densityHD, echo=TRUE, warning=FALSE, fig.cap='The density plots after the data is transformed by asins transformation with the optimum cofactors.'---- ## transform CD3 and CD4 channels in all samples HD.VS = transFlowVS(HD, channels=c('CD3', 'CD4'), cofactors) ## density plot (from flowViz package) densityplot(~CD3+CD4, HD.VS, main="Transfromed CD3 and CD4 channels in HD data") ## ----ITN, echo=TRUE, warning=FALSE, fig.keep='high', fig.show='hold', out.width='.49\\linewidth', fig.cap='Transforming two fluorescence channels in the ITN data. Bartlett\'s statistics (Y-axis) is computed from density peaks after data is transformed by different cofactors (X-axis). An optimum cofactor is obtained where Bartlett\'s statistics is minimum (indicated by red circles).'---- ## Example 2: ITN data from flowStats package suppressMessages(library(flowStats)) data(ITN) # identify lymphocytes ITN.lymphs = fsApply(ITN,lymphs, list("FS"=c(200, 600),"SS"=c(0, 400)), "FSC", "SSC",FALSE) ## identify optimum cofactor for CD3 and CD4 channels cofactors = estParamFlowVS(ITN.lymphs[1:5],channels=c('CD3', 'CD4')) ## ----densityITN, echo=TRUE, warning=FALSE, fig.cap='The density plots after the data is transformed by asins transformation with the optimum cofactors.'---- ## transform CD4 channel in all samples ITN.VS = transFlowVS(ITN.lymphs, channels=c('CD3', 'CD4'), cofactors) ## density plot (from flowViz package) densityplot(~CD3+CD4, ITN.VS, main="Transfromed CD3 and CD4 channels in ITN data") ## ----microVS, echo=TRUE, warning=FALSE, fig.width=5, fig.height=5-------- suppressMessages(library(vsn)) data(kidney) kidney.microVS = microVS(exprs(kidney)) #variance stabilization ## ----vsn, echo=TRUE, warning=FALSE, fig.width=4.5, fig.height=4, fig.show='hold', fig.align='center', fig.cap='Variance stabilization of the Kidney microarray data by flowVs and vsn packages.'---- suppressMessages(library(vsn)) data(kidney) kidney.vsn = vsn2(exprs(kidney)) #variance stabilization by vsn plotMeanSd(kidney.microVS, main="Kidney data: VS by flowVS") plotMeanSd(exprs(kidney.vsn), main="Kidney data: VS by vsn") ## ----sessionInfo, results = 'asis', eval = TRUE, echo = TRUE------------- toLatex(sessionInfo())